wtf is sota-models?

This project, called "sota-models," is a collection of cutting-edge deep learning network designs bundled together so they can be tested for speed. Instead of training these networks to solve a problem, the repository is set up to measure how fast each design runs when processing data. Think of it as a benchmarking track for different artificial intelligence architectures to see which ones are the most efficient on your hardware. To use it, you run a simple command that tells the software which network design you want to test. By default, it runs on your computer's main processor, but you can add a simple flag to the command to tell it to use a graphics card instead. The tool then processes the network and gives you a speed profile, helping you understand the performance tradeoffs of each design before you commit to using one for a real product. This would be most useful for engineers or researchers who are trying to decide which deep learning architecture to use for a new application. If you are building something that needs to process data quickly, like real-time image recognition, you want to know which models will meet your speed requirements without requiring too much computing power. The repository gives you a quick way to compare those options directly. The README also includes a specific note for running these tests on computers with a certain type of processor setup. If your machine has a mix of slower and faster processing cores, it explains how to force the software to use only the fast cores, which prevents the system from being slowed down by the weaker ones. Beyond this, the documentation is quite sparse and focuses mostly on the basic commands needed to run the tests.